The State of Health Prediction of Li-Ion Batteries Based on ISMA-HKELM

Accurately predicting the State of Health (SOH) of lithium-ion batteries (LIBs) is essential to ensure their long-term stable and safe operation. This paper proposes a novel model, the ISMA-HKELM, which is an Improved Slime Mould Algorithm (ISMA)-optimized Hybrid Kernel Extreme Learning Machine (HKE...

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Autors principals:	Yao Jiang, Yuanzhao Deng, Yan Ai, Yuesheng Zhu
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2026-03-01
Col·lecció:	Energies
Matèries:	lithium-ion battery the state of health improved slime mould algorithm hybrid kernel extreme learning machine algorithm optimization
Accés en línia:	https://www.mdpi.com/1996-1073/19/7/1627
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